The nature of mathematics from cultural, historical and logical viewpoints, stressing relationships between mathematics and other disciplines. Recommended for humanities, fine arts and education majors. Does not count toward the major. Includes emphasis on basic quantitative skills. Fulfills numeric/symbolic engagement requirement. Offered in 3-week semesters.

Descriptive statistics; probability and probability distributions; sampling and sampling distributions; confidence intervals and hypothesis testing; correlation and regression analysis. Emphasis on application and interpretation. Recommended for social science and pre-professional majors; does not count toward the major. Fulfills numeric/symbolic engagement requirement. Offered in 14-week semesters.

Pre-calculus analysis of algebraic, exponential, and logarithmic functions. Recommended for life sciences; does not count towards major. Fulfills numeric/symbolic engagement requirement. Offered in 14-week semesters.

Pre-calculus analysis of algebraic, exponential, logarithmic, trigonometric and inverse trigonometric functions. Does not count toward the major. Fulfills numeric/symbolic engagement requirement. Offered in 14-week semesters.

Analysis and application of trigonometric functions, complex numbers, and vectors. Recommended for natural sciences; does not count towards major. Fulfills quantitative literacy requirement (1998). Numeric/symbolic engagement requirement (2019).

May also be offered at 250, 350 and 450 levels. 150 and 250 level courses fulfill the numeric/symbolic engagement requirement.

Algorithms, recursion, induction, sequences and series, combinatorics, counting techniques, and proof techniques particularly as related to the mathematics of computing. Fulfills numeric/symbolic engagement requirement (2019).

Limits, derivatives, and integrals of functions of a single variable with applications to optimization. Fulfills numeric/ symbolic engagement requirement.

Techniques of integration, indeterminate forms, infinite series - including Taylor series. Applications to differential equations, physical systems, and probability.

Sequences, series, and power series. Functions of multiple variables, partial differentiation, and multiple integrals. Application to probability and physical sciences. Calculus of vector-valued functions and vector fields. Line integrals, surface integrals, and major theorems concerning their calculation. Fulfills numeric/symbolic engagement requirement (2019).

Algebra of vectors, valued functions, vector fields. Differentiation, line and surface integrals. Greens?, Stokes?, and Divergence Theorems.

Axiomatic development of an elementary mathematical system, stressing the logical nature and structure of mathematics.

Scientific Computing is a course designed jointly by Math & Physics faculty to serve students of the sciences. We will use the programming language Python and a variety of the standard libraries (especially numpy, matplotlib, vpython) to do analyses and simulations. Emphasizes the documentation and presentation of results to peers. Satisfies elective credit for Analytics major. Taught in the 3-week semester.

May also be offered at 150, 350 and 450 levels.

May also be offered at 360 and 460 levels.

Seminars are provided to allow and encourage students and faculty members to pursue topics of mutual interest beyond the scope of regular classes. Seminars may be arranged as extensions of existing courses, as special topics courses, as undergraduate research projects or as honors projects. Students must prearrange seminars with faculty members before classes begin; no student may register for a seminar without prior departmental approval. Seminars carry from one to four credits and may be repeated for credit with permission of the department. Lower- and upper-level seminars in selected topics.

May also be offered at the 390 level.

4 credit hours. Introduction to ordinary differential equations, elementary techniques of solution, theory of existence and uniqueness. Other topics may include systems of ordinary differential equations using matrix techniques, introduction to partial differential equations, Fourier and Laplace transforms and application to solutions.

Fundamentals of the analysis and interpretation of statistical data, theory and application. Includes descriptive statistics; probability; discrete and continuous random variables, their probability, density and moment-generating function; joint, marginal and conditional probability and density functions of several random variables; sampling distributions; estimation; hypothesis testing. Fulfills quantitative literacy requirement (1998).

Introduction to systems of linear equations, matrices, linear spaces and linear transformations, including applications of these concepts to other areas of mathematics and to other fields.

This course is a hands-on introduction to business analytics. In this course, students will learn to convert quantitative data into information that can be used to help guide business/government decision making. This course provides students with the fundamental concepts and tools needed to understand the emerging role of business analytics in organizations. Students will apply modern data mining tools to various data sets in an analytical software environment. Emphasis is placed on concepts, applications, and interpretation of results as well as professional skills like communication, teamwork, and presentation.

This course is a hands-on introduction to statistical learning methods. Statistical learning refers to a set of tools for modeling and understanding complex data sets. This course covers many statistical learning methods such as estimation, linear and multiple regression, clustering and classification, ANOVA, and non-parametric analysis. In addition to programming techniques for statistical learning methods, students will work on professional skills including communication, teamwork, and presentation. The course is to be taught in the 3 week semester.

4. Topics in point-set, geometric, general or algebraic topology with content dependent on student and instructor interest. Suggested for majors emphasizing theoretical mathematics.

Topics chosen from Euclidean, hyperbolic, elliptic, projective, affine, etc., geometry emphasizing axiomatic development and/or physical application with content dependent upon student interest and background. Especially recommended for students interested in mathematics education. Fulfills quantitative literacy requirement (1998).

Techniques, theory, computer programming and application of approximations of zeros of functions, solutions to systems of equations, integrals and ordinary differential equations. Suggested for majors emphasizing applied mathematics or mathematical physics. Fulfills quantitative literacy requirement (1998). Recommended: MATH 212 Discrete Math or MATH 231 Foundations of Mathematical Proof and CTIS 210 Introduction to Computer Programming.

Study of algebraic structures such as groups, rings and fields and their morphisms. Suggested for majors emphasizing theoretical mathematics or interested in mathematics education. Recommended: MATH 325 Linear Algebra.

Rigorous study of real functions including topics from limits, sequences, series, differentiation and integration. Suggested for majors emphasizing theoretical mathematics or mathematical physics.

Topics in point-set, geometric, general or algebraic topology with content dependent on student and instructor interest. Suggested for majors emphasizing theoretical mathematics. Fulfills quantitative literacy requirement (1998).

Seminars are provided to allow and encourage students and faculty members to pursue topics of mutual interest beyond the scope of regular classes. Seminars may be arranged as extensions of existing courses, as special topics courses, as undergraduate research projects or as honors projects. Students must prearrange seminars with faculty members on or before the first day of classes; no student may register for a seminar without prior departmental approval. Seminars carry 1 ? 4 credits and may be repeated for credit with permission of the department. Lower- and upper-level seminars in selected topics.